The federal report found that barely half of Georgia’s high schools offered geometry; just 66 percent offered Algebra I.

Those data are just plain wrong, said Matt Cardoza, a spokesman for the Department of Education. The state requires Algebra I, geometry and Algebra II for graduation, so all high schools have to offer the content — but they typically integrate the material into courses titled Math 1, 2, 3 and 4, Cardoza said. He surmised that somedistricts checked “no” on the survey because their course titles didn’t match the federal labels, even if the content did.

“It’s the name issue,” Cardoza said. “I think schools just didn’t know what to say.”

Ah, data quality has reared its ugly head...and now everyone is freaking out about the perceived inequity of math offerings.

So, here's the deal. Suppose you're a working at a high school. You offer an algebra class...but you might not call it

*Algebra I*. You might call it just plain

*Algebra*. Or

*Algebraic Thinking*. Heck, you might even have

*Advanced Algebra*or

*Honors Algebra*or

*9th Grade Algebra*. At the school level, this distinction doesn't really matter. The school has a master schedule, assigns highly qualified teachers to whatever sections it has that they identify as math. When a new student shows up and needs a math credit, everything in the student information system enables the placement.

But that isn't the end of the story. There's another layer of data that few---maybe just the registrar or district data manager---will ever see. There's a whole taxonomy of course codes determined by the National Center for Education Statistics. These course codes are collected by the state and are part of the district student information system. But because the district doesn't use them for anything---remember, they have their own labels---not many pay attention to what fills those fields.

Here is one example (click to embiggen):

These are the math classes for Bellevue High School for the 2012 - 13 school year. (data source here). Columns 4 - 6 include state course labels---the invisible ones---and 7 and 8 are designated for the district. So, let's dig into the last row ("Mathematics-Other") and see what the district is lumping in there.

Notice that in the second column from the right---District Course Title---we have things like

*Alg I Seminar, Gmtry Seminar, G-Alg 1 Seminar*. We can't see the syllabi for these classes, but it's likely that algebra and geometry concepts are being taught. Kids are getting math credits and are being scheduled into math classes, but a data pull at a state or federal level will never see these.

It gets worse. Start digging through "miscellaneous" categories, and you start to see things like this:

The state course code on the left says English Language and Literature-Other...and the district has assigned biology, chemistry, physics, nanotechnology, and more to this category. Even assuming these are courses for English language learners, special education students, or other population, it's still science content---it doesn't belong in English. At this level, data quality is a real mess.

But what to do? After all, it doesn't make a difference to the district. They have their own codes and credit systems. It does make a difference to anyone outside of that system. It's public data. Anyone can use it for any reason---from bureaucrats trying to make decisions about allocations to think-tanks sounding the alarm about equity.

All of this mumbo jumbo doesn't mean that schools with larger minority populations aren't being underserved. Considering the other ways we shortchange these students, it doesn't seem unlikely that access to a rigorous curriculum would be on the list. I suspect, however, that noise in the data quality is hiding the true signal.

I tell teachers all the time that paying attention to data quality is the simplest way to have a direct effect on policy. You might not think that attendance you took in first period matters...but it does. As it rolls up, districts will make decisions about how they make resources...states will consider policy. How many absences before a student should be considered "at-risk"? What strategies work best to improve attendance rates? What should be the legal consequences for students or parents when kids don't attend school? All the little pieces of data matter. If you want better policy, we need better data quality.